The present invention relates generally to image processing systems and techniques, and more particularly to an interactive registration technique for aligning images based upon a division of at least one of the images into a hierarchical meshed segmentation.
Many imaging systems and techniques are known and are currently used in different arts. For example, in medical imaging, various modalities of imaging systems may be employed for creating useful images of anatomies, abnormalities, lesions, aneurysms, atrophies, and so forth. In general, such imaging systems operate in accordance with a particular physical effect and gather image data which can be processed to create useful images. Most modern modalities for such imaging systems are based upon collection of digital data which is processed and stored, and which may be manipulated by various post-processing techniques. In the medical field, for example, such imaging systems include X-ray systems, computed tomography systems, magnetic resonance imaging systems, positron emission tomography systems, ultrasound systems, and so forth. These and other modalities of digital imaging system exist in other arts, particularly in industrial inspection, package and baggage inspection, defense applications, and so forth.
In the medical field, many clinical decisions are made based upon or derived from analysis information available from one or more image dataset. In the radiology domain, for example, this typically involves spatially registering the datasets such that the areas of interest are aligned. From a practical standpoint, images are analyzed either by manual reading, by analysis through automated algorithms, or a combination of these techniques. To permit comparison and contrast of images, alignment or registration of the images is often in order. That is, because the images may be made on different subjects, or at different times on the same subject, as well as on different imaging modalities, characteristics, anatomies, features and so forth visible in the images may not be properly aligned with one another. Image registration can present extremely difficult mathematical problems involved in moving or altering one or both images to be compared, while respecting the integrity of the data so as to avoid confusion or misinterpretation. It should be borne in mind that these problems are presented not only in the medical field, but in any other field in which image registration is performed.
By way of example, in medical image analysis, referring physicians often request that images to be made and interpreted for a specific purpose. Such purposes can range from the detection, assessment, analysis of progression or regression of various abnormalities or disease states. Multiple datasets for images may be used for comparison purposes, such as with and without contrast agents, or for the analysis of changes overtime, or still further for combination with certain functional datasets. Many of these comparisons and contrasts are made based upon changes within a single patient overtime although similar comparisons can be made between patients, or between a standard or reference image, sometimes referred to as in “atlas” image, and an image for a specific patient. To perform the necessary analysis using multiple datasets, the datasets must first be accurately and robustly registered. Here again, applications outside of the medical field requiring alignment or comparison of an image or a feature within an image with a standard or reference feature often sesitates a similar registration process.
While many context-specific algorithms that exist, the purpose of which is to register multiple datasets, the variability in virtually all sources of image data results in no particular algorithm functioning exactly as desired for all registration problems. Moreover, factors, such as scaling, noise, motion, partial voluming, and so forth may create artifacts that hamper the accuracy and precision of registration algorithms.
In many practical applications, the main issue with results obtained from a registration algorithm is not whether it is accurate based upon a numerical criterion, but rather how a human user, who is the final arbiter in the matter, perceives it. Furthermore, there is generally a need “correct” the registration results based upon the numerical criteria employed. Such corrections are not easily achieved by manual registration techniques. Such techniques commonly permit a human technician to provide points, lines, services, volumes and so forth before the registration process. Interactive registration methods involving global transforms also fall short of user expectation. In all such cases there is a need to provide a flexible yet intuitive tool to a human user to facilitate speedy registration, which may be supplemented by machine computation.